A Computational Analysis of the Negative Impact of Cigarette Smoking on Human Population In Imo State

Smoking is a practice in which a substance most commonly called Tobacco or Cannabis is burnt and the smoke tasted or inhaled. Recognition of the consequences of cigarette smoking and abuse on physical and mental health as well as socio-occupational life are necessary steps for initiating appropriate action to reduce the harm or dangers resulting from smoking. This work was motivated by the observed and anticipated negative health burden with its concomitant socio-economic consequences which the nation is bound to face if systematic efforts are not made now to control the growing problem of cigarette smoking. Three methodologies have been combined in the execution of this research. The first methodology involved conducting the clinical test to determine the independent assessment of impact of smoking using Digital Display Nicotine Tester (DDNT). Secondly, sample populations of people treated at the Imo State University Teaching Hospital from diseases emanating from smoking were collected, statistically analyzed using Statistical Packages for Social Sciences (SPSS).Relevant coefficients were extracted and deployed for the coding of the simulation model. Thirdly, simulation software was developed using the indices collected from the statistical software to assess the impact of smoking on the population in the next 50 years. This is to assist policy formlators and decision makers on what public policy should be in place to stem possible health catastrophe that may occur as a result of uncontrolled consumption. The software simulation follows a stochastic model

Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme

Artificial Intelligence (AI) has been a source of great intrigue and has spawned many questions regarding the human condition and the core of what it means to be a sentient entity. The field has bifurcated into so-called “weak” and “strong” artificial intelligence. In weak artificial intelligence reside the forms of automation and data mining that we interact with on a daily basis. Strong artificial intelligence can be best defined as a “synthetic” being with cognitive abilities and the capacity for presence of mind that we would normally associate with humankind. We feel that this distinction is misguided. First, we begin with the statement that intelligence lies on a spectrum, even in artificial systems. The fact that our systems currently can be considered weak artificial intelligence does not preclude our ability to develop an understanding that can lead us to more complex behavior. In this research, we utilized neural feedback via electroencephalogram (EEG) data to develop an emotional landscape for linguistic interaction via the android's sensory fields which we consider to be part and parcel of embodied cognition. We have also given the iCub child android the instinct to babble the words it has learned. This is a skill that we leveraged for low-level linguistic acquisition in the latter part of this research, the slightly stronger artificial intelligence goal. This research is motivated by two main questions regarding intelligence: Is intelligence an emergent phenomenon? And, if so, can multi-modal sensory information and a term coined called “co-intelligence” which is a shared sensory experience via coupling EEG input, assist in the development of representations in the mind that we colloquially refer to as language? Given that it is not reasonable to program all of the activities needed to foster intelligence in artificial systems, our hope is that these types of forays will set the stage for further development of stronger artificial intelligence constructs. We have incorporated self-organizing processes - i.e. Kohonen maps, hidden Markov models for the speech, language development and emotional information via neural data - to help lay the substrate for emergence. Next, homage is given to the central and unique role played in intellectual study by language. We have also developed rudimentary associative memory for the iCub that is derived from the aforementioned sensory input that was collected. We formalized this process only as needed, but that is based on the assumption that mind, brain and language can be represented using the mathematics and logic of the day without contradiction. We have some reservations regarding this statement, but unfortunately a proof is a task beyond the scope of this Ph.D. Finally, this data from the coupling of the EEG and the other sensory modes of embodied cognition is used to interact with a reservoir computing recurrent neural network in an attempt to produce simple language interaction, e.g. babbling, from the child android

Influence of Aqueous Leaf Extract of Senna Alata L, Roxb. on the Germination and Seedling Growth of Beans, Maize and Groundnut

Plants extracts have been known to either promote or inhibit plant growth and germination. The influence of aqueous leaf extract of Senna alata (L.) Roxb on the germination and seedling growth of maize (Zea mays), Beans (Phaseolus vulgaris) and Groundnut (Arachis hypogea) were investigated. The experiment was carried out at Michael Okpara University of Agriculture Umudike, green house situated besides the University apex Library. The leaves of Senna alata were air dried, ground, mixed with water and then used for the treatment. Concentrated extracts and its dilutions 1:1, 1:2.5, 1:5 v/v was used as treatments and water served as control. Each treatment was replicated three times. The experiment was designed using Randomized Completely Block Design (RCBD) and the results obtained were statistically analyzed using ANOVA. The result obtained showed that all treatments significantly (P<0.05) inhibited germination in maize except for 1:2.5, which improved germination. Also, the treatments significantly (P<0.05) inhibited germination in beans except for treatments 1:1 and 1:5, which improved germination. However, all treatments significantly (P<0.05) improved germination in groundnut. There was significant increase (P<0.05) in plant height and dry weight of the plant compared with the control. This indicates that seedling growth of Beans, Maize and Groundnut were positively affected by the aqueous leaf extract of S. alata. High concentration of the extract leads to increased plant height and dry matter of the plant. Further study is needed to ascertain the bio-activity of S. alata. Keywords: Influence, Aqeouos leaf extract, Germination. DOI: 10.7176/JBAH/9-24-04 Publication date: December 31st 2019

Dynamic Spectrum Allocation Access Using Cognitive Radio Networks in a Maritime

The maritime environment is unique due to radio wave propagation over water, surface reflection and wave obstruction. In dealing with the challenging maritime environment, a dynamic spectrum allocation access using cognitive radio network through optimization is proposed. Existing works in this area are limited in performance due to the long duration in achieving the probability of false alarm. Matched filtering technique which is known as the optimum method for detection of primary users (PUs) faces the challenge of large power consumption as various receiver’s algorithm are needed to be executed for detection. This work provides a platform that enables minimum energy utilization by secondary users (SUs) thereby, enhancing throughput. An algorithm for throughput maximum in spectrum allocation was developed and used based on demand based model. The implementation of the developed model was carried out using Java program and the spectrum analysis using long distance path loss model and adaptive modulation code to estimate the minimum bandwidth of the secondary users. A simulation of cognitive radio mesh network for the testing and validation of the demand based algorithm preference, and also the cognitive radio network traffic was carried out using Cisco packet tracer and results shown on MATLAB. Simulation results indicate that using the demand based algorithm, the throughput rose with time and almost stabilized. This increase and steady throughput indicates effectiveness in the algorithm which shows that the PUs and SUs activities increase as holes’ detection effort varies, unlike that of genetic algorithm where the throughput rose gradually, got to a peak value at certain time and then fell which indicates instability in the variation of the throughput. Also, the average throughput of the demand based algorithm is far greater than that of genetic algorithm which shows that demand based algorithm outperforms the genetic by a far greater percentage. The percentage of optimization is approximately 26%

Familial adenomatous polyposis with synchronous invasive colonic carcinomas and metastatic jejunal adenocarcinoma in a Nigerian male

Familial adenomatous polyposis is rare. Three cases were previously reported in Nigeria. An intriguing feature of this case is an ulcerated jejunal carcinoma which was metastatic rather than synchronous carcinoma. This patient presented with partial large bowel obstruction and the pathological analysis revealed 4 invasive adenocarcinomas, 3 in the colon and 1 in the jejunum (Dukes stage D). Palliative pancolectomy and jejunal tumour resection with chemotherapy was offered to him. He died eight months after surgery from disease progression. The challenges of managing a hereditary cancer syndrome in a resource poor country are highlighted

Factors associated with long intensive care unit (ICU) admission among inpatients with and without diabetes in South Western Sydney public hospitals using the New South Wales admission patient data collection (2014-2017)

Despite a campaign of effective educational interventions targeting knowledge, attitudes, and prevention, Human Immunodeficiency-Virus/Acquired Immune Deficiency Syndrome (HIV/AIDS) continues to be a significant public health issue in India, with Mizoram reporting the highest HIV/AIDS cases in 2018–2019. In this study, we extracted Mizoram state from the National Family Health Survey Fourth Series (NFHS-4) 2015–2016 datasets and investigated factors associated with respondents’ knowledge, attitudes, and prevention towards HIV/AIDS. The sample included 3555 adults aged 15–49 years residing in Mizoram, North-east India. Respondents who reported having ever heard of HIV/AIDS was 98%. Multivariate analysis indicated that the probability of having inadequate knowledge of HIV/AIDS was higher among those with no schooling, who were illiterate, of non-Christian faiths, belonging to backward tribes or caste, from poor households, and those who lived in rural areas, not exposed to media. The odds of mother-to-child transmission (PMTCT) of HIV/AIDS transmission was high among females (AOR = 3.12, 95% CI 2.34–4.16), respondents aged 35–39 years (AOR = 1.74, 95% CI 1.05–2.87) and those belonging to other backward class. The HIV/AIDS knowledge of respondents was found to be encouraging as the majority (98%) were considered to have a good level of understanding of the condition. An educational intervention to reduce the number of adults 15–49 years infected with HIV/AIDS in Mizoram should target those from low socioeconomic groups, those from non-Christian religions, and those from other backward classes

Factors associated with non-utilization of postnatal care among newborns in the first 2 days after birth in Pakistan : a nationwide cross-sectional study

Background: Recent data indicated that approximately four in every ten newborns in Pakistan do not receive postnatal care (PNC) services in the first 48 hours after delivery. Objectives: This study aimed to identify factors associated with the non-utilization of PNC for newborns in Pakistan using the 2017–18 Pakistan Demographic and Health Survey (PDHS). Methods: This was a cross-sectional analytical study utilizing data from 3887 live-born newborns recorded in the 2017–18 PDHS. Non-utilization of PNC was assessed against a set of independent factors using multilevel logistic regression analysis, and the population attributable risk estimates of factors associated with non-utilization of PNC were also calculated. Results: There were 1443 newborns (37%) in Pakistan whose mothers did not utilize PNC check-ups in the first 2 days after delivery. The non-utilization of PNC was largely attributable to newborns delivered at non-health facilities 53% (47% to 59%) and those born to uneducated women 27% (13% to 38%). Adjusted analyses indicated that newborns with higher birth order and with a birth interval of more than 2 years, women who perceived their baby to be small at birth, women with no formal education and those living in regional areas of Khyber Pakhtunkhwa and Federally Administered Tribal Areas were significantly associated with non-utilization of PNC services. Conclusions: Tailored health messages by community health workers, including door-to-door visits on utilizing health facilities through pregnancy to the postnatal periods, are needed and should target places of low socioeconomic status, including educationally disadvantaged women from regional areas of Pakistan

Analysis of in-hospital mortality among people with and without diabetes in South Western Sydney public hospitals (2014-2017)

Background: Diabetes is a major public health problem affecting about 1.4 million Australians, especially in South Western Sydney, a hotspot of diabetes with higher than average rates for hospitalisations. The current understanding of the international burden of diabetes and related complications is poor and data on hospital outcomes and/or what common factors influence mortality rate in people with and without diabetes in Australia using a representative sample is lacking. This study determined in-hospital mortality rate and the factors associated among people with and without diabetes. Methods: Retrospective data for 554,421 adult inpatients was extracted from the population-based New South Wales (NSW) Admitted Patient Data over 3 financial years (from 1 July 2014–30 June 2015 to 1 July 2016–30 June 2017). The in-hospital mortality per 1000 admitted persons, standardised mortality ratios (SMR) were calculated. Binary logistic regression was performed, adjusting for potential covariates and co-morbidities for people with and without diabetes over three years. Results: Over three years, 8.7% (48,038 people) of admissions involved people with diabetes. This increased from 8.4% in 2014–15 to 8.9% in 2016–17 (p = 0.007). Across all age groups, in-hospital mortality rate was significantly greater in people with diabetes (20.6, 95% Confidence intervals CI 19.3–21.9 per 1000 persons) than those without diabetes (11.8, 95%CI 11.5–12.1) and more in men than women (23.1, 95%CI 21.2–25.0 vs 17.9, 95%CI 16.2–19.8) with diabetes. The SMR for those with and without diabetes were 3.13 (95%CI 1.78–4.48) and 1.79 (95%CI 0.77–2.82), respectively. There were similarities in the factors associated with in hospital mortality in both groups including: older age (> 54 years), male sex, marital status (divorced/widowed), length of stay in hospital (staying longer than 4 days), receiving intensive care in admission and being admitted due to primary respiratory and cardiovascular diagnoses. The odds of death in admission was increased in polymorbid patients without diabetes (28.68, 95%CI 23.49–35.02) but not in those with diabetes. Conclusions: In-patients with diabetes continue to have higher mortality rates than those without diabetes and the Australian population. Overall, similar factors influenced mortality rate in people with and without diabetes, but significantly more people with diabetes had two or more co-morbidities, suggesting that hospital mortality may be driven by those with pre-existing health/comorbidities. Urgent measures in primary care to prevent admissions among people with multiple co-morbidities are needed